Alternative statistical techniques for aiding SFRA diagnostics in transformers

Badgujar, Ketan P.; Maoyafikuddin, Mohammad; Kulkarni, S.V.

doi:10.1049/iet-gtd.2011.0268

Cited by 78 publications

(56 citation statements)

References 5 publications

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“…The answer 1 indicates a rejection of the null hypothesis at the 5% significance level and 0 indicates a failure to reject the null hypothesis at the 5% significance level. x and y need not be vectors of the same length [24,25].…”

Section: Statistical Testsmentioning

confidence: 99%

Statistical approach for interpretation of power transformers frequency response analysis results

Behjat¹,

Mahvi²

2015

IET Science, Measurement & Technology

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In spite of many research efforts on fault diagnosis using frequency response analysis (FRA) method, there is still no universally accepted and systematic interpretation technique for these tests and 'expert opinion' is often sought when any damaging trend is observed as a result of fault occurrence. This study deals with statistical criteria for interpretation of the FRA results and presents a number of statistical and mathematical indicators that have not been used so far. A measurement setup accompanied by a transformer as a test object, on which winding faults are imposed, completes the test setup for performing the FRA measurements. The parameters are applied to the experimental FRA measurements and the results are compared by a simple normalising equation. Finally, the indicators which are adding more objectivity and transparency to interpretation of the FRA results are presented. Sweep frequency response analysis (SFRA) method is used in this study because of its efficiency and simplicity. It was found through this research work that F-test, which introduced in this study for the first time, has higher sensitivity, and the differences between the normal and faulty responses of the transformers' windings is more reflected in this parameter compared with the other ones.

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Section: Statistical Testsmentioning

confidence: 99%

Statistical approach for interpretation of power transformers frequency response analysis results

Behjat¹,

Mahvi²

2015

IET Science, Measurement & Technology

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“…They are widely described in the literature [9,[14][15][16][17][18][19][20][21][22], therefore only basic information of their application have been presented in Table 1. Formulas that are designed for assessment in one test setup only, e.g., from Chinese standard DL/T911-2004, which is to be used in end-to-end test setup, have been omitted.…”

Section: Fra Measurements and Results Interpretationmentioning

confidence: 99%

Cross Test Comparison in Transformer Windings Frequency Response Analysis

Banaszak

Szoka

2018

Energies

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Frequency Response Analysis (FRA) is an important tool used for diagnostic measurements of power transformers. Standard test configuration applied in the industry is the end-to-end open test setup; however, an interwinding capacitive configuration is also used. This paper presents a method-Cross Test Comparison (CTC)-for simultaneous analysis of results coming from both the mentioned test setups. Such an approach could offer a more sensitive tool for detecting some faults; moreover, it takes into consideration the influence of both voltage sides of a transformer in a one test result. The authors have used several indices to quantitatively assess the test results and proposed new approach to data interpretation. CTC method was tested using data from measurements performed in three cases: a unit tested in laboratory with introduced controlled deformations; transformers measured under industrial conditions; and a transformer with FRA changes resulting from tap-changer operations. The results showed that CTC method is more effective at detecting faults on the basis of FRA measurements.

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“…To compare the difference of master curves with measured curves the following functions are used: [27] ASLE, as expressed in (13), compares the data on a logarithmic scale. The ideal value of ASLE is 0.…”

Section: Comparison Methodsmentioning

confidence: 99%

Condition assessment of transformer insulation using dielectric frequency response analysis by artificial bee colony algorithm

Bigdeli

Aghajanloo

2016

Archives of Electrical Engineering

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Transformers are one of the most important components of the power system. It is important to maintain and assess the condition. Transformer lifetime depends on the life of its insulation and insulation life is also strongly influenced by moisture in the insulation. Due to importance of this issue, in this paper a new method is introduced for determining the moisture content of the transformer insulation system using dielectric response analysis in the frequency domain based on artificial bee colony algorithm. First, the master curve of dielectric response is modeled. Then, using proposed method the master curve and the measured dielectric response curves are compared. By analyzing the results of the comparison, the moisture content of paper insulation, electrical conductivity of the insulating oil and dielectric model dimensions are determined. Finally, the proposed method is applied to several practical samples to demonstrate its capabilities compared with the well-known conventional method.

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Alternative statistical techniques for aiding SFRA diagnostics in transformers

Cited by 78 publications

References 5 publications

Statistical approach for interpretation of power transformers frequency response analysis results

Statistical approach for interpretation of power transformers frequency response analysis results

Cross Test Comparison in Transformer Windings Frequency Response Analysis

Condition assessment of transformer insulation using dielectric frequency response analysis by artificial bee colony algorithm

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